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TrakkrMCP

MCP Server

Connect Trakkr to ChatGPT, Claude, Claude Code, Cursor, VS Code, Codex, and other MCP-compatible AI assistants. Query your visibility data conversationally - no code required.

What is MCP?

The Model Context Protocol is an open standard that lets AI assistants connect to external tools. Once Trakkr is connected, you ask questions in plain English and your assistant calls the right tools behind the scenes - backed by live data from your account.

Natural language
Ask in plain English. No endpoints, no parameters.
68 tools
Visibility, competitors, reports, crawler workflows.
Hosted or local
Hosted connectors for chat apps, local setup for developer tools.

Get connected

Pick your AI assistant - the install steps and code panel update to match. Claude uses the hosted connector at https://api.trakkr.ai/mcp; developer tools use the local setup shown in the code panel. ChatGPT support is coming soon.

  1. 1
    Get your connect token

    Generate an MCP connect token from Settings → Developer. Tokens start with mcp_connect_ and are shown once.

    MCP access is included on every paid plan. The direct REST API and sk_live_ keys remain Scale-only.
  2. 2
    Create the Claude connector

    Copy https://api.trakkr.ai/mcp into Claude's connector setup. When Claude opens the Trakkr authorization page, paste your MCP connect token there.

    Claude MCP docs
  3. 3
    Restart and ask away

    Finish the Claude connection flow, then open a new chat. Try one of the prompts below to verify everything works.

Keep your connect token out of source control. Don't commit config files containing your token - add them to .gitignore or use your client's secret-input pattern.

Trakkr stores redacted MCP activity logs: tool names, timing, status, and safe argument/result summaries for security, support, and product improvement. Full assistant conversations are not stored.

What you can ask

Your assistant picks the right tools automatically. Some prompts to try:

“How is my brand doing in AI search?”
“Which competitors are gaining ground?”
“What content should I create next?”
“Show me citation trends over the last quarter”
“Run a diagnosis on "best CRM for startups"”
“How does Perplexity describe my brand vs competitors?”
“Summarize my latest research run - visibility, top competitors, and the prompts I missed”
“Run a topic snapshot on "enterprise pricing pages" and tell me when it's done”
“What Reddit threads should I jump into this week?”
“List my active workflows and what fired in the last seven days”
“Show me unread notifications and mark them all as read”
“Wire a webhook to https://example.com/hook for visibility_changed and citation_gained”
“Compare brands ABC and XYZ on visibility, citations, and actions for the last 30 days”
“What's in my knowledge base and what's the most recent published article?”
“Across every brand I manage, what are the top 10 highest-impact actions right now?”
“How has my brand narrative drifted over the last quarter?”
“Using Trakkr research, what page types actually get cited in AI search?”
“Does llms.txt actually help me get cited?”

For multi-step queries, your assistant chains tools together - e.g. fetching your brand ID, then pulling scores, then comparing against a competitor - all in one turn.

Want to turn a finding into a shipped fix? The MCP Cookbook shows how to chain Trakkr with your other MCP servers (GitHub, your CMS, Slack, Search Console), so the gap Trakkr finds gets fixed in the same chat.

Available tools

68 tools across 12 groups. Each maps to an endpoint in the Trakkr API. Open a group to see parameters and views.

Resources

Resources pull Trakkr context into a chat with no tool call. In clients that support them, @-mention a resource (for example @trakkr://brand/<id>/briefing). Each is read-only and bounded, so reading one never triggers analysis or compute.

Your brand (paste-ready briefings)

Dense markdown you can @-attach to any chat, so the model gets your brand right.brand-book is the one to paste.

trakkr://brandThe index of your brands and their IDs, each linked to the briefings below. Start here to find a brand ID.
trakkr://brand/{id}/brand-bookPaste-ready context so any AI describes the brand right: what it is, how AI frames it now, what to set straight, and the proof.
trakkr://brand/{id}/snapshotLatest AI visibility: headline scores, a by-model table, and the prompts where you win and lose.
trakkr://brand/{id}/citation-gapsPrompts where AI cites a rival but not you, ranked, with who gets cited and what to publish.
trakkr://brand/{id}/promptsThe AI-search questions Trakkr is tracking for this brand, active and paused.
Your brand (live state, JSON)
trakkr://brandsThe brands you can access, with the IDs the per-brand resources need.
trakkr://brand/{id}/briefingHeadline visibility and trend, plus the open-action snapshot.
trakkr://brand/{id}/actionsThe brand top open actions, most impactful first.
trakkr://brand/{id}/changesWhat moved in the last week (the get_changes digest).
trakkr://brand/{id}/latest-reportThe most recent generated report.
Data & research

Every rival shows you your own numbers. These expose Trakkr’s public research on what actually gets brands cited, drawn live from our /data studies.

trakkr://dataIndex of the research briefings below.
trakkr://data/what-gets-citedWhich page types earn AI citations, and owned vs third-party.
trakkr://data/crawler-personalitiesWhat each AI bot actually fetches and reads.
trakkr://data/llms-txt-truthThe honest null result: llms.txt shows no citation lift.
trakkr://data/schema-advantageHow structured data correlates with getting cited.
trakkr://data/citation-decayHow fast AI citations fade.
trakkr://data/model-divergenceWhere AI models disagree on who to recommend.
trakkr://data/playbookThe synthesis: the rules for getting cited, with links.

Workflows

Workflows are server prompts that appear as slash commands in your assistant’s prompt menu the moment Trakkr connects. Each one chains the right tools and research into a single finished briefing, most important first. Arguments are optional; leave the brand out and the workflow resolves it for you.

/weekly-reviewbrand, period
Your Monday brief: visibility and trend, who is gaining, the biggest citation gaps, and the easy wins, as five tight bullets.
/competitor-teardownbrand, competitor
Where a rival beats you, where you beat them, and three concrete moves to close the gap.
/citation-gap-planbrand
The prompts you are losing, cross-referenced with the research on what actually gets cited, ending in a ranked plan of what to publish.
/content-briefbrand, topic
A citation-optimised outline plus the on-page schema to include for one piece, ready to hand to a writing tool.
/setup-trackingdomain
Onboarding in one chat: confirm the brand, set its market, then propose a starter set of prompts to track and create them on your say-so.
/trakkr-watchbrand_id, since
A watch playbook: pulls what moved for a brand, summarizes it plainly, and offers next steps. Pass the last cursor to see only what is new.

Troubleshooting

Package

Package
trakkr-mcp
Version
0.5.0
Python
≥ 3.10
License
MIT

Code example

Claudehttps://api.trakkr.ai/mcp

Add Trakkr as a custom connector in Claude, then paste your MCP connect token when prompted.

  1. 1In Claude, open Customize > Connectors.
  2. 2Choose Add custom connector and use https://api.trakkr.ai/mcp as the remote MCP server URL.
  3. 3Click Connect, then paste your MCP connect token on the Trakkr authorization page when Claude prompts you.
Claude connector docs
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